CoachLayer vs Terra and Sahha: three layers, one stack.
These are complements, and pretending otherwise would be marketing. Terra moves wearable data into your backend. Sahha turns signals into scores with contributing factors. CoachLayer turns training and recovery data into the sentence the athlete actually acts on: train, modify or rest, and why, with the numbers.
If you only need one layer, buy that layer. The comparison worth reading is what each layer refuses to do, because that is where teams lose quarters.
Data, scores, coaching: who stops where.
| Layer | Vendor | Ships | Deliberately does not ship | Public pricing |
|---|---|---|---|---|
| Data pipe | Terra | Normalized health and fitness data from 500+ wearables and apps, delivered by API and webhooks, plus derived scores. | Interpretation. The payload is normalized data and derived metrics, and what it means for training is your problem. | From $399/mo on the annual plan ($499 monthly), 100,000 credits included, roughly 200 credits per active user per month, overage from $0.005 per credit. |
| Scores | Sahha | Phone and wearable signals turned into 0 to 100 scores (sleep, activity, readiness among them) with contributing factors, plus a trends and comparisons insights API. | The narrative. A readiness of 62 with three contributing factors still needs someone to write the brief and the training decision. | Self-serve tiers with a free start; usage-based beyond. |
| Coaching | CoachLayer | Readiness briefs with an explicit train, modify or rest directive, workout analysis, weekly reports, adaptive programming, coach chat. Benchmarked on production traffic. | Data acquisition. We do not connect to a single wearable; your data arrives in the request, from your backend or from a pipe like the ones on this page. | Credit-metered tiers on the pricing table, sandbox free |
Vendor facts checked September 2026 (Terra) and August 2026 (Sahha); list prices are theirs, not our restatement of a sales quote.
Scores in, coaching out.
Terra + CoachLayer
Terra webhooks land sleep, HRV and activity in your backend; your backend passes them with the training log into a readiness brief call. Terra is the supplier lane here, not the rival one.
Sahha + CoachLayer
Sahha’s scores and factors make excellent structured input for the brief: the score says 62, the brief says what to do about it in the athlete’s language. Nothing in either contract fights the other.
Neither + CoachLayer
Plenty of apps already hold their training data and HealthKit reads. Then no pipe is needed at all: the coaching layer runs on what you have, and a thin data layer can come later.
The up-stack question, answered honestly.
The data and score vendors are visibly climbing toward interpretation: richer derived metrics, insight digests, trend narratives. As of September 2026, none of them ships narrative coaching with an explicit training directive as a product, which is the layer this page is about. If that changes, this comparison changes, and we will update it rather than defend it. Our bet is not that they cannot climb; it is that a coaching layer extracted from a shipped training product, with a production benchmark attached, is a different thing to catch up with than a feature checkbox.
Your data layer is solved. Coaching is the gap.
Whatever pipe you use, the brief is one POST away. Sandbox is free, no card.
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